In this session, we focus on the pre-processing and post-processing workflow in OpenFOAM, covering essential tools for case setup, mesh inspection, and efficient visualization of CFD results. Special emphasis is given to optimizing post-processing using ParaView’s Python scripting, enabling automation, reproducibility, and faster analysis of large datasets.
Instructor: Dr. Pratyush Kumar (IIT Bombay)
📌 What You Will Learn:
🔷 Pre-Processing Tools in OpenFOAM
Case directory structure and file organization
Mesh generation and inspection tools
Field initialization and boundary-condition verification
🔷 Post-Processing Tools in OpenFOAM
Built-in OpenFOAM post-processing utilities
Sampling, probes, and field data extraction
Managing large transient and parallel datasets
🔷 ParaView for CFD Visualization
Loading OpenFOAM cases efficiently in ParaView
Common filters for CFD analysis (slices, contours, streamlines)
Best practices for handling large simulations
🔷 Optimizing Post-Processing with Python Scripting
Introduction to ParaView’s Python interface
Automating visualization and data extraction tasks
Batch processing of multiple time steps or cases
Improving reproducibility and reducing manual effort
🎯 Who Should Watch?
CFD practitioners, researchers, and OpenFOAM users who want to streamline their pre- and post-processing workflow and leverage Python scripting in ParaView for efficient and scalable CFD analysis.
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